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UID:01a1989d-2ca0-71c0-b457-4796dae77e8e@www.devopschat.co
DTSTAMP:20261106T134339Z
DTSTART:20190924T153000Z
DTEND:20190924T163000Z
SUMMARY:Houston DevOps Meetup: VMWare Wavefront and 3D Microservices Observ
 ability
DESCRIPTION:The modern application landscape is changing fast! A microservi
 ces architecture modularizes your application where each service can be bu
 ilt and scaled independently of the other. Individual developers can itera
 te fast and provide continuous delivery of their microservice. But this al
 so means more complexity\, more chaos\, more moving parts in production at
  a faster cadence. Microservices architecture can be a boon for developers
  but a bane for SREs. Without a sophisticated observability platform\, the
  promise of microservices\, unfortunately\, is broken!\n\nMicroservices ob
 servability focuses on a tight data integration of three key data sources\
 , correlating time-series metrics\, histogram distribution\, and distribut
 ed tracing information. With a unified view\, developers and SREs get a tr
 ue 3-dimensional (metrics\, histograms\, traces) view they need to monitor
 \, troubleshoot\, and profile their microservices application performance.
  Under the hood\, a microservices application is composed of popular open 
 source frameworks. The beauty of microservices is that you’re not tied t
 o one programming language. With a single\, unified “observability SDK
 ”\, SREs and developers can quickly use out-of-the-box metrics\, histogr
 ams\, and traces for all the popular frameworks and\nlanguages. Out-of- th
 e-box implies taking your polyglot application that is\ncompletely un-inst
 rumented\, plug in the relevant SDKs and instantly start seeing metrics\, 
 histograms and traces lit up on our built-in dashboard UI.\nIn this talk\,
  we will detail our journey toward implementing this 3D observability expe
 rience for our SREs and developers\, where we analyze and visualize RED me
 trics (Requests\, Errors\, and Duration) for our microservices-based SaaS 
 application\, used by large enterprises worldwide. The duration\, in this 
 case\, is a histogram comprising minute\, hour and day distributions as fi
 rst-class citizens in ourbackend store so the data can be sliced and diced
  that data with statistical functions (min\, max\, mean\, median\, p75\, p
 95\, p99\, p99.99) on those distributions.\n\nWe integrated distributed tr
 acing that provides language agnostic context propagation across all our m
 icroservices. We also derive metrics and histograms (i.e. RED metrics) fro
 m tracing spans so that we can quickly indicate top requests\, top failed 
 requests\, and slowest operations. All this information can be visualized 
 byour sophisticated dashboards built specifically so that our SREs can tri
 age root cause faster in production.\n\nIn conclusion\, by getting to 3D m
 icroservices observability\, our SREs and\ndevelopers finally have a compl
 ete picture of the microservices application that will empower them to not
  only get a pulse of the overall health of their application but also dril
 l down into the specific misbehaving microservice thus troubleshooting pro
 blems in production\nfaster.\n\nhttps://www.devopschat.co/meetings/houston
 -devops-meetup-vmware-wavefront-and-3d-microservices-observability
URL:https://www.devopschat.co/meetings/houston-devops-meetup-vmware-wavefro
 nt-and-3d-microservices-observability
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